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Abstract For the purpose of producing datasets for regional-scale climate change research and application, the NCEP–NCAR reanalysis for the period 1948–2005 was dynamically downscaled to hourly, 10-km resolution over California using the Regional Spectral Model. This is Part I of a two-part paper, describing the details of the downscaling system and comparing the downscaled analysis California Reanalysis Downscaling at 10 km (CaRD10) against observation and global analysis. An extensive validation of the downscaled analysis was performed using station observations, Higgins gridded precipitation analysis, and Precipitation-Elevation Regression on Independent Slopes Model (PRISM) precipitation analysis. In general, the CaRD10 near-surface wind and temperature fit better to regional-scale station observations than the NCEP–NCAR reanalysis used to force the regional model, supporting the premise that the regional downscaling is a viable method to attain regional detail from large-scale analysis. This advantage of CaRD10 was found on all time scales, ranging from hourly to decadal scales (i.e., from diurnal variation to multidecadal trend). Dynamically downscaled analysis provides ways to study various regional climate phenomena of different time scales because all produced variables are dynamically, physically, and hydrologically consistent. However, the CaRD10 is not free from problems. It suffers from positive bias in precipitation for heavy precipitation events. The CaRD10 is inaccurate near the lateral boundary where regional detail is damped by the lateral boundary relaxation. It is important to understand these limitations before the downscaled analysis is used for research.
Kanamitsu et al. (Thu,) studied this question.
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